Wireless substrate-like sensor

ABSTRACT

A wireless substrate-like sensor is provided to facilitate alignment and calibration of semiconductor processing systems. The wireless substrate-like sensor includes an optical image acquisition system that acquires one or more images of targets placed within the semiconductor processing system. Analysis of images of the targets obtained by the wireless substrate-like sensor provides position and/or orientation information in at least three degrees of freedom. An additional target is affixed to a known location within the semiconductor processing system such that imaging the reference position with the wireless substrate-like sensor allows the measurement and compensation for pick-up errors.

CROSS-REFERENCE OF CO-PENDING APPLICATIONS

The present application is a divisional of and claims priority of U.S.patent application Ser. No. 10/356,684, filed Jan. 31, 2003, whichapplication claims priority to previously filed provisional applicationSer. No. 60/354,551, filed Feb. 6, 2002, entitled WAFER-LIKE SENSOR.

BACKGROUND OF THE INVENTION

Semiconductor processing systems are characterized by extremely cleanenvironments and extremely precise semiconductor wafer movement.Industries place extensive reliance upon high-precision robotic systemsto move substrates, such as semiconductor wafers, about the variousprocessing stations within a semiconductor processing system with therequisite precision.

Reliable and efficient operation of such robotic systems depends onprecise positioning, alignment, and/or parallelism of the components.Accurate wafer location minimizes the chance that a wafer mayaccidentally scrape against the walls of a wafer processing system.Accurate wafer location on a process pedestal in a process chamber maybe required in order to optimize the yield of that process. Preciseparallelism between surfaces within the semiconductor processing systemsis important to ensure that minimal substrate sliding or movement duringtransfer from a robotic end effector to wafer carrier shelves,pre-aligner vacuum chucks, load lock elevator shelves, process chambertransfer pins and/or pedestals. When a wafer slides against a support,particles may be scraped off that cause yield loss. Misplaced ormisaligned components, even on the scale of fractions of a millimeter,can impact the cooperation of the various components within thesemiconductor processing system, causing reduced product yield and/orquality.

This precise positioning must be achieved in initial manufacture, andmust be maintained during system use. Component positioning can bealtered because of normal wear, or as a result of procedures formaintenance, repair, alteration, or replacement. Accordingly, it becomesvery important to automatically measure and compensate for relativelyminute positional variations in the various components of asemiconductor processing system.

In the past, attempts have been made to provide substrate-like sensorsin the form of a substrate, such as a wafer, which can be moved throughthe semiconductor processing system to wirelessly convey informationsuch as substrate inclination and acceleration within the semiconductorsystem. As used herein, “substrate-like” is intended to mean a sensor inthe form of substrate such as a semiconductor wafer, a Liquid CrystalDisplay glass panel or reticle. Attempts have been made to providewireless substrate-like sensors that include additional types ofdetectors to allow the substrate-like sensor to measure a host ofinternal conditions within the processing environment of thesemiconductor processing system. Wireless substrate-like sensors enablemeasurements to be made at various points throughout the processingequipment with reduced disruption of the internal environment as well asreduced disturbance of the substrate handling mechanisms and fabricationprocesses (e.g.: baking, etching, physical vapor deposition, chemicalvapor deposition, coating, rinsing, drying etc.). For example, thewireless substrate-like sensor does not require that a vacuum chamber bevented or pumped down; nor does it pose any higher contamination risk toan ultra-clean environment than is suffered during actual processing.The wireless substrate-like sensor form factor enables measurements ofprocess conditions with minimal observational uncertainty.

A dire need currently exists for systems that offer the benefits ofwireless substrate-like sensors while facilitating the acquisition ofand compensation for information related to positional variations ofcomponents within a semiconductor processing system. Although wirelesssubstrate-like sensors currently provide limited information such asinclination and acceleration, they do not provide the requiredpositional information. Technicians must still make subjective judgmentsto adjust the relative positions of the various components within thesemiconductor processing system in order to ensure that such componentscooperate to provide extremely careful substrate processing. Currentlyavailable sensors do not enable automatic adjustment of positionaloffsets between components of a semiconductor processing system.

SUMMARY OF THE INVENTION

A wireless substrate-like sensor is provided to facilitate alignment andcalibration of semiconductor processing systems. The wirelesssubstrate-like sensor includes an optical image acquisition system thatacquires one or more images of targets or objects within thesemiconductor processing system. Analysis of images of the targetsobtained by the wireless substrate-like sensor provides usefulinformation such as position, presence/absence, value and/or orientationin at least three degrees of freedom. An additional target can beaffixed to a known location within the semiconductor processing systemsuch that analyzing the reference position image with the wirelesssubstrate-like sensor allows the measurement and compensation for pickupinduced positional errors.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagrammatic view of a semiconductor wafer processenvironment.

FIG. 2 is a top perspective view of a wireless substrate-like sensor inaccordance with embodiments of the present invention.

FIG. 3 is a bottom view of a wireless substrate-like sensor inaccordance with embodiments of the present invention.

FIG. 4 is a diagrammatic view of central portion 120 in accordance withembodiments of the present invention.

FIG. 5 is a top perspective view of a holster for maintaining a wirelesssubstrate-like sensor in accordance with embodiments of the presentinvention.

FIG. 6 is a top plan view of a target for use with embodiments of thepresent invention.

FIG. 7 is a diagrammatic view of a vector transformation in accordancewith embodiments of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

While aspects the prior art have provided wireless substrate-likesemiconductor sensors, the information provided by such sensors has beenlimited. To significantly facilitate semiconductor processing systemalignment and calibration requires substantially more functionality thanhas been heretofore provided by wireless substrate-like sensors.Specifically, no wireless substrate-like sensors have providedinformation allowing calculation of very precise positions andorientations of components within the semiconductor processing system.This feature as well as many others will be apparent upon reading thediscussion below.

FIG. 1 is a diagrammatic view of a semiconductor wafer processingenvironment including a wafer container 100, robot 102 and systemcomponent station 104 illustrated diagrammatically as simply a box.Wafer container 100 is illustrated containing three wafers 106, 108, 110and wireless substrate-like sensor 112 in accordance with embodiments ofthe present invention. As is apparent from FIG. 1, sensor 112 ispreferably embodied in a form factor allowing it to be moveable withinthe semiconductor wafer processing environment in the same manner aswafers themselves. Accordingly, embodiments of the present inventionprovide a substrate-like wireless sensor having a height low enough topermit the substrate-like sensor to move through the system as if itwere a substrate such as a wafer. For example, a height of less thanabout 9.0 mm is believed to be acceptable. Preferably, the sensor has aweight of less than two wafers, for example, a weight of less than about250 grams is believed to be acceptable. A stand-off distance of about 25mm is believed to meet the requirements of most applications; howeversome applications may require a different stand-off. As used herein“stand-off” is the nominal distance from the bottom of the sensor to thetarget. The diameter of the sensor preferably matches one of thestandard semiconductor wafer diameters, such as, 300 mm, 200 mm or 150mm.

Sensor 112 is preferably constructed from dimensionally stablematerials. In order for the substrate-like sensor to accurately measurea three-dimensional offset, it is important for the sensor to deform ina manner similar to that of an actual substrate. Common wafer dimensionsand characteristics may be found in the following specification: SEMIM1-0302, “Specification for Polished Monocrystaline Silicon Wafers”,Semiconductor Equipment and Materials International, www.semi.org. Thecenter of a 300 mm silicon wafer supported at its edges will sagapproximately 0.5 mm under its own weight. The difference in thedeformation of the sensor and the deformation of an actual wafer shouldbe much less than the accuracy of sensor measurement. In a preferredembodiment, the stiffness of the substrate-like sensor results in adeflection that is nearly identical to that of an actual silicon wafer.Therefore, no compensation is required to correct for any differentialdeflection. Alternatively, a compensation factor may be added to themeasurement. Similarly, the weight of the substrate-like sensor willalso deflect its support. Substrate supports include, but are notlimited to: end effectors, pedestals, transfer pins, shelves, etc. Thedifferential support deflection will be a function both of thedifference in weights of the sensor and a substrate as well as themechanical stiffness of the substrate support. The difference betweendeflection of the support by the sensor and that by a substrate shouldalso be much less than the accuracy of sensor measurement, or thedeflection difference should be compensated by a suitable calculation.

In the prior art, technicians have iteratively adjusted the alignment ofa vacuum transfer robot end effector with a process chamber pedestal byviewing them after removing the lid of the process chamber or through atransparent window in the lid. Sometimes a snuggly fitting fixture orjig must first be placed on the process pedestal to provide a suitablereference mark. The substrate-like sensor enables an improved,technician assisted, alignment method. The substrate-like sensorprovides an image of the objects being aligned without the step ofremoving the cover and with greater clarity than viewing through awindow. The wireless substrate-like sensor saves significant time andimproves the repeatability of alignment.

A wireless substrate-like sensor can transmit an analog camera image byradio.

A preferred embodiment uses a machine vision sub-system of asubstrate-like wireless sensor to transmit all or a portion of thedigital image stored in its memory to an external system for display oranalysis. The external system can also be configured to store a numberof such digital images. The display may be located near the receiver orthe image data may be relayed through a data network for remote display.In a preferred embodiment, the camera image is transmitted encoded as adigital data stream to minimize degradation of image quality caused bycommunication channel noise. The digital image may be compressed usingany of the well known data reduction methods in order to minimize therequired data rate. The data rate may also be significantly reduced bytransmitting only those portions of the image that have changed from theprevious image. The substrate-like sensor or the display may overlay anelectronic cross hair or other suitable mark to assist the technicianwith evaluating the alignment quality.

While vision-assisted teaching is more convenient than manual methods,technician judgment still affects the repeatability and reproducibilityof alignment. The image acquired by a substrate-like wireless sensorcamera may be analyzed using many well-known methods, includingtwo-dimensional normalized correlation, to measure the offset of apattern from its expected location. The pattern may be an arbitraryportion of an image that the vision system is trained to recognize. Thepattern may be recorded by the system. The pattern may be mathematicallydescribed to the system. The mathematically described pattern may befixed at time of manufacture or programmed at the point of use.Conventional two-dimensional normalized correlation is sensitive tochanges in the pattern image size. When a simple lens system is used,magnification varies in proportion to object distance. Enhanced patternoffset measurement performance may be obtained by iteratively scalingeither the image or the reference. The scale that results in the bestcorrelation indicates the magnification, provided the size of thepattern is known, or the magnification, as used when the referencepattern was recorded, is known.

When the correspondence between pixels in the image plane to the size ofpixels in the object plane is known, offsets may be reported in standardunits of measure that are easier for technicians or machine controllersto interpret than arbitrary units such as pixels. For example, theoffset may be provided in terms of millimeters such that the operatorcan simply adjust the systems by the reported amount. The computationsrequired to obtain the offset in standard units may be performedmanually, by an external computer, or preferentially within the sensoritself. When the sensor extracts the required information from an image,the minimum amount of information is transmitted and the minimumcomputational burden is placed on the technician or external controller.In this way objective criteria may be used to improve the repeatabilityand reproducibility of the alignment. Automated offset measurementimproves the reproducibility of alignment by removing variation due totechnician judgment.

During alignment and calibration of semiconductor processing equipment,it is not only important to correctly position an end effector relativeto a second substrate supporting structure, it is also important toensure that both substrate supporting structures are parallel to oneanother. In a preferred embodiment, a machine vision subsystem of awireless substrate-like sensor is used to measure the three dimensionalrelationship between two substrate supports. For example: a robotic endeffector may hold a wireless substrate-like sensor in close proximity tothe transfer position and a measurement of the three dimensional offsetwith six degrees of freedom may be made from the sensor camera to apattern located on an opposing substrate support. One set of six degreesof freedom includes yaw, pitch, and roll as well as displacement alongthe x, y, and z axes of the Cartesian coordinate system. However, thoseskilled in the art will appreciate that other coordinate systems may beused without departing from the spirit and scope of the invention.Simultaneous measurement of both parallelism and Cartesian offset allowsa technician or a controller to objectively determine satisfactoryalignment. When a controller is used, alignments that do not requiretechnician intervention may be fully automated. Automated alignments maybe incorporated into scheduled preventive maintenance routines thatoptimize system performance and availability.

In a very general sense, operation and automatic calibration of roboticsystem 102 is performed by instructing robot 102 to select and conveysensor 112 to reference target 114. Once instructed, robot 102 suitablyactuates the various links to slide end effector 116 under sensor 112 tothereby remove sensor 112 from container 100. Once removed, robot 102moves sensor 112 directly over reference target 114 to allow an opticalimage acquisition system (not shown in FIG. 1) within sensor 112 toobtain an image of reference target 114. Based upon a-priori knowledgeof the target pattern, a three dimensional offset between the sensor andtarget 114 is measured. The measurement computation may occur within thesensor or an external computer. Based upon a-priori knowledge of theprecise position and orientation of reference target 114, the threedimensional offset thereof can be analyzed to determine the pick-uperror generated by robot 102 picking up sensor 112. Either internal orexternal computation allows the system to compensate for any errorintroduced by the pick-up process of sensor 112.

This information allows sensor 112 to be used to acquire images ofadditional targets, such as target 117 on system component 104 tocalculate a precise position and orientation of system component 104.Repeating this process allows the controller of robot 102 to preciselymap exact positions of all components within a semiconductor processingsystem. This mapping preferably generates location and orientationinformation in at least three and preferably six degrees of freedom (x,y, z, yaw, pitch and roll). The mapping information can be used by atechnician to mechanically adjust the six degree of freedom location andorientation of any component with respect to that of any othercomponent. Accurate measurements provided by the substrate-like wirelesssensor are preferably used to minimize or reduce variability due totechnician judgment. Preferably, this location information is reportedto a robot or system controller which automates the calibration process.After all mechanical adjustments are complete; the substrate-like sensormay be used to measure the remaining alignment error. The six degrees offreedom offset measurement may be used to adjust the coordinates ofpoints stored in the memories of the robot and/or system controllers.Such points include, but are not limited to: the position of anatmospheric substrate handling robot when an end effector is located ata FOUP slot #1 substrate transfer point; the position of an atmosphericsubstrate handling robot when an end effector is located at a FOUP slot#25 substrate transfer point; the position of an atmospheric substratehandling robot when an end effector is located at a substratepre-aligner substrate transfer point; the position of an atmosphericsubstrate handling robot when an end effector is located at a load locksubstrate transfer point; the position of an atmospheric substratehandling robot when an end effector is located at a reference targetattached to the frame of an atmospheric substrate handling system; theposition of a vacuum transfer robot when its end effector is located ata load lock substrate transfer point; the position of a vacuum transferrobot when an end effector is located at a process chamber substratetransfer point; and the position of a vacuum transfer robot when an endeffector is located at a target attached to the frame of a vacuumtransfer system.

An alternative embodiment of the present invention stores and reportsthe measurements. Real-time wireless communication may be impractical insome semiconductor processing systems. The structure of the system mayinterfere with wireless communication. Wireless communication energy mayinterfere with correct operation of a substrate processing system. Inthese cases, sensor 112 can preferably record values as it is conveyedto various targets, for later transmission to a host. When sensor 112,using its image acquisition system, or other suitable detectors,recognizes that it is no longer moving, sensor 112 preferably recordsthe time and the value of the offset. At a later time, when sensor 112is returned to its holster (shown in FIG. 6) sensor 112 can recall thestored times and values and transmit such information to the host. Suchtransmission may be accomplished by electrical conduction, opticalsignaling, inductive coupling or any other suitable means. Store andreport operation of the wireless substrate-like sensor potentially:increases the reliability, lowers the cost and shortens a regulatoryapproval cycle for the system. Moreover, it avoids any possibility thatthe RF energy could interact with sensitive equipment in theneighborhood of the sensor and its holster. Store and report operationcan also be used to overcome temporary interruptions of a real-timewireless communication channel.

FIG. 2 is a top perspective view of a wireless substrate-like sensor 118in accordance with embodiments of the present invention. Sensor 118differs from sensor 112 illustrated in FIG. 1 solely in regard to themanner in which weight reduction is effected. Specifically, sensor 112employs a number of struts 118 to suspend a central sensor portion 120within an outer periphery 122 that can accommodate standard wafer sizes,such as 300 millimeter diameter wafers. In contrast, sensor 118 employsa number of through-holes 124 which also provide weight reduction tosensor 118. Other patterns of holes may be used to accomplish thenecessary weight reduction. Additional weight reduction designs are alsocontemplated including, for example, portions of the sensor that arehollow, and/or portions that are filled with light-weight materials.Both sensor 112 and sensor 118 employ central region 120. A portion ofthe underside of central portion 120 is disposed directly over an accesshole 126 as illustrated in FIG. 3. Access hole 126 allows illuminator128 and image acquisition system 130 to acquire images of targetsdisposed below sensor 118 as sensor 118 is moved by robot 102.

FIG. 4 is a diagrammatic view of portion 120 in accordance withembodiments of the present invention. Portion 120 preferably includes acircuit board 140 upon which a number of components are mounted.Specifically, battery 142 is preferably mounted on circuit board 140 andcoupled to digital signal processor (DSP) 144 via power managementmodule 146. Power management module 146 ensures that proper voltagelevels are provided to digital signal processor 144. Preferably, powermanagement module 146 is a power management integrated circuit availablefrom Texas Instrument under the trade designation TPS5602. Additionally,digital signal processor 144 is preferably a microprocessor availablefrom Texas Instruments under the trade designation TMS320C6211. Digitalsignal processor 144 is coupled to memory module 148 which can take theform of any type of memory. Preferably, however, memory 148 includes amodule of Synchronous Dynamic Random Access Memory (SDRAM) preferablyhaving a size of 16M×16. Module 148 also preferably includes flashmemory having a size of 256K×8. Flash memory is useful for storing suchnon-volatile data as programs, calibration data and/or additional othernon-changing data as may be required. The random access memory is usefulfor storing volatile data such as acquired images or data relevant toprogram operation.

Illumination module 150, which preferably comprises a number of LightEmitting Diodes (LEDs), and image acquisition system 152 are coupled todigital signal processor 144 through camera controller 154. Cameracontroller 154 facilitates image acquisition and illumination thusproviding relevant signaling to the LEDs and image acquisition system152 as instructed by digital signal processor 144. Image acquisitionsystem 152 preferably comprises an area array device such as a ChargeCoupled Device (CCD) or Complementary Metal Oxide Semiconductor (CMOS)image device coupled preferably to an optical system 156, which focusesimages upon the array. Preferably, the image acquisition device isavailable from Kodak under the trade designation KAC-0310. Digitalsignal processor 144 also preferably includes a number of I/O ports 158,160. These ports are preferably serial ports that facilitatecommunication between digital signal processor 144 and additionaldevices. Specifically, serial port 158 is coupled to radio-frequencymodule 162 such that data sent through port 158 is coupled with externaldevices via radio frequency module 162. In one preferred embodiment,radio frequency module 162 operates in accordance with the well-knownBluetooth standard, Bluetooth Core Specification Version 1.1 (Feb. 22,2001), available from the Bluetooth SIG (www.bluetooth.com). One exampleof module 162 is available from Mitsumi under the trade designationWML-C11.

Detectors 164 may take any suitable form and provide relevantinformation regarding any additional conditions within a semiconductorprocessing system. Such detectors can include one or more thermometers,accelerometers, inclinometers, compasses (Magnetic field directiondetectors), light detectors, pressure detectors, electric field strengthdetectors, magnetic field strength detectors, acidity detectors,acoustic detectors, humidity detectors, chemical moiety activitydetectors, or any other types of detector as may be appropriate.

FIG. 5 illustrates an optional holster 180 which can be used to storeand maintain a wireless substrate-like sensor when such sensor is not inuse. Holster 180 provides a convenient way to recharge the internalpower storage device of the wireless sensor. Preferably, holster 180includes suitable contacts to electrically couple to the wirelesssubstrate-like sensor to thereby recharge the power source within thesensor. Such coupling can occur via any suitable methods including:inductive, photovoltaic, capacitive, and conductive methods.

FIG. 6 is a diagrammatic view of a target useful with embodiments of thepresent invention. Important features of target 190 are that a visualtarget is provided having a known size and geometry such that an imagethereof can be processed to calculate x, y, z positions, as well as yaw,pitch and roll. Such six-degree positional calculations have heretoforenot been accommodated with wireless substrate-like sensors. Preferably,target 190 has a size of 50 mm×50 mm and includes four circular marks192 which have a known size, geometry and positional relationship withrespect to one another. Careful imaging and processing of target 190 canallow a system to calculate a vector to transform positions from that ofthe image acquisition system (wireless substrate-like sensor) to thetarget (semiconductor processing system component or reference marker).

For example, suppose the exact position of a flat surface in threedimensions must be found from a two-dimensional image of the surfacetaken by a camera. The position of the surface can be described by threevectors illustrated in FIG. 7 as follows: A and B are two vectors in theplane of the surface, which together describe the orientation of thesurface. These can be thought of as axes of a local coordinate system onthe surface. C is a vector from the image acquisition system to areference point on the surface, which describes the position of thesurface. (In fact C measures from a specific point inside the lens ofthe image acquisition system; the exact position of this point dependson the design of the image acquisition system.)

If the surface has some markings on it, such as indicia 192, a point inthe marking pattern can be described in the surface coordinates by twonumbers (u, v). The position of this point in three-dimensional space isthen described by the vector equation:P=C+u·A+v·B  EQ. 1The position (x, y) in the camera's image of this point is determined bythe perspective transformation:x=k·P _(x) /P _(z); and y=k·P _(y) /P _(z)where k is a constant related to the field of view of the imageacquisition system.

The relationship between the position of the mark on the surface and theposition of the mark on the image can be obtained by combining theseequations:x·(C _(z) +u·A _(z) +v·B _(z))=k·(C _(x) +u·A _(x) +v·B _(x)); andy·(C _(z) +u·A _(z) +v·B _(z))=k·(C _(y) +u·A _(y) +v·B _(y)).

If a known pattern is used, u and v for each mark are known constants.Also, x and y for each mark can be measured from the image, and k can bedetermined by calibrating the camera.

One method of calibrating the camera is to image a mark at a knownposition relative to the camera, (Px, Py, Pz). If (x, y) is the positionof the mark in the camera image, the camera magnification can becomputed by eitherk=x*Pz/Px,ork=y*Pz/Py.

More accurate values for k can be determined if necessary by makingseveral measurements and using statistical techniques.

If a pattern with four marks, as illustrated in FIG. 6, is used, thisresults in a system of eight linear equations which can then be solvedfor these nine unknownsC_(x), C_(y), C_(z), A_(x), A_(y), A_(z), B_(x), B_(y) and B_(z).

Once these nine values are known, the position and orientation in spaceof the surface can be computed. Because there are only eight equationsand nine unknowns, one more constraint must be applied to find a uniquesolution. The lack of uniqueness exists because the same image willresult from changing the system by any scaling factor—a large targetwill look exactly same to the image acquisition system as a small targetclose up. This can be seen in the equations by noting that multiplyingall three vectors A, B, C by a constant does not change these equations.This means that the final constraint cannot be added by simply usingfive marks to get an additional three linear equations. Instead, aconstraint on the size of the system should be used. The easiestconstraint to chose is a constraint such as the absolute value |A|=1which requires that the units used to measure u and v are the same asthe units used on the vectors A, B, C.

The solution to these eight linear equations and one non-linear equationcan be found for any particular pattern of markings (except for a fewspecial cases such as all four marks in a straight line). The resultscan then be used in combination with simple image processing techniquesto create a computer program which automatically calculatesthree-dimensional position and orientation of the surface from videoimages.

In summary, calculation of the position and orientation of target 190 isdone by choosing a target with four easily found marks which can beattached to a surface of interest. Then, the method described above isemployed and the chosen positions of the marks are used to create asystem of eight equations in nine variables. Then, the system is solvedto obtain expressions for eight of the nine components of the positionvectors in terms of the ninth. For example, solve for A, B, and the xand y components of C in terms of C_(z). The following steps areperformed by the sensor each time it performs a measurement:

1) digitize an image of the target on the surface;

2) use standard image processing techniques such as blob analysis tofind the reference marks in the image;

3) use the expressions described above to obtain eight components of theposition vectors assuming the ninth is 1.0;

4) compute the length of A and divide all components by this length toproduce correct values for the vectors A, B, C; and

5) optionally convert the results for the orientation vectors A and B torotation angles and add an offset to C such that the position isreported relative to some reference point other than the lens of theimage acquisition system. The method described above is an illustrativesolution only, and it is contemplated that other approaches to findingthe position of a surface using a two-dimensional image can be usedwithout departing from the spirit and scope of the invention.

Although the present invention has been described with reference topreferred embodiments, workers skilled in the art will recognize thatchanges may be made in form and detail without departing from the spiritand scope of the invention. Although embodiments of the presentinvention have been described with respect to acquiring optical imagesof calibration targets and processing such images to ascertain positionand orientation information in at least three degrees of freedom,additional optical features can be provided. For example, the wirelesssubstrate-like sensor in some embodiments, is adapted to recognizecharacters and/or barcodes.

1. A wireless substrate-like sensor assembly used to perform calibrationof a semiconductor processing system, the sensor assembly comprising: awireless substrate-like sensor including: a processor; an internal powersource; and an image acquisition system; a holster adapted tomechanically couple to the sensor to store the sensor when not in use;an automatic calibration target including: at least four target indicia,wherein the at least four target indicia are related to one anotherthrough a known relationship; and wherein the automatic calibrationtarget is mountable to at least one station of the system; and whereinthe sensor is adapted to provide location information relative to atleast one automatic calibration target in at least two degrees offreedom.
 2. The assembly of claim 1 additionally including anillumination source.
 3. The system of claim 1 additionally including awireless communication device.
 4. The assembly of claim 1 wherein theprocessor is a digital signal processor.
 5. The assembly of claim 1,wherein the sensor has a diameter of about 300 mm.
 6. The assembly ofclaim 1, wherein the sensor has a diameter of about 200 mm.
 7. Theassembly of claim 1, wherein the sensor has a diameter of about 150 mm.8. The assembly of claim 1, wherein the sensor has a diameter of about450 mm.
 9. The assembly of claim 1, wherein the sensor is adapted toprovide location information relative to at least one automaticcalibration target in at least three degrees of freedom.
 10. Theassembly of claim 1, wherein the sensor is adapted to provide locationinformation relative to at least one automatic calibration target in atleast six degrees of freedom.
 11. The assembly of claim 1, wherein thesensor provides the location information to a technician.
 12. Theassembly of claim 1, wherein the sensor provides the locationinformation to a system controller.
 13. The assembly of claim 1, whereinthe sensor provides the location information to a robot controller. 14.The assembly of claim 1, wherein the sensor is constructed from silicon.15. The assembly of claim 1, wherein the holster charges the internalpower source of the sensor when they are coupled together.
 16. Theassembly of claim 1, wherein the holster communicates with the sensor.17. The assembly of claim 1, wherein each automatic calibration targetincludes a background with a high contrast to the indicia.
 18. Theassembly of claim 1 wherein the sensor records values for latertransmission to a host and wherein, the sensor uses its imageacquisition system to recognize when it is no longer moving and thenrecords the time and the value of the offset.
 19. The assembly of claim1 wherein the sensor recognizes characters.
 20. The assembly of claim 1wherein the sensor recognizes bar codes.